Five Ways Automation Speeds Up Big Data Deployments

Operational Costs

Users expecting lower operational costs by using Hadoop software and infrastructure are surprised to find they must spend enormous sums for software support and maintenance in the form of recurring "subscription" fees. Automation significantly offsets IT resource requirements, support and maintenance costs associated with Hadoop deployment. And as the size of the Hadoop cluster grows, so do the savings associated with automation.

Hadoop has come a long way since its inception. From its early days as a platform, to an index for the Web, it has evolved to its current interactive, real-time and batch processing capabilities spanning gigabytes to petabytes of content. However, as enterprises move Hadoop from pilot to production environments, they are finding the "on-boarding" process slow and complicated.

Along with Hadoop, other Big Data technologies are complex and challenging to set up, sometimes generating large costs for support and maintenance. This is not a scalable model for customers who want to efficiently move Hadoop into production networks. That said, here's a breakdown of the five ways automation speeds up the Big Data on-boarding process from Big Data management and security vendor Zettaset.

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